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• Could not read frame error when trying to decompress mp4 file with ffmpeg and Python's threading module

  23 janvier 2017, par mdornfe1

  I’m training constitutional neural networks with video data. So far the bottle neck of my application is decompressing the mp4 files before passing the images to the CNN for training. I had the idea to try to have multiple cpu threads decompress the images concurrently and having one thread pass images to the CNN for training. I made a class VideoStream which makes connection to the mp4 file using the ImageIO module which is built on top of ffmpeg. The structure of my program is a follows :

  1) Generate random ints which represent the frame numbers of the mp4 file that will be used in training. Store these ints in list frame_idxs.

  2) Pass this list of ints and an empty list called frame_queue to the worker function decompress_video_data.

  3) Each worker function makes a connection to the mp4 file using VideoStream.

  4) Each worker function then pops of elements of frame_idxs, decompresses that frame, and then stores that frame as numpy array in list frame_queue.

  Here is the code

  import numpy as np
  
  import os, threading, multiprocessing
  
  
  
  
  
  def decompress_video_data(frame_queue, frame_idxs, full_path):
  
      vs = VideoStream(full_path)
  
      while len(frame_idxs) >1 0:
  
          i = frame_idxs.pop()
  
          frame = vs[i]
  
          frame_queue.append(frame)
  
  
  
  video_folder = '/mnt/data_drive/frame_viewer_client'
  
  video_files = os.listdir(video_folder)
  
  video_file = video_files[0]
  
  full_path = os.path.join(video_folder, video_file)
  
  vs = VideoStream(full_path)
  
  
  
  num_samples = 1000
  
  batch_size = 1
  
  frame_queue = []
  
  decompress_threads = []
  
  frame_idxs = list(np.random.randint(0, len(vs), 
  
      size = batch_size * num_samples))
  
  num_cores = multiprocessing.cpu_count()
  
  
  
  for n in range(num_cores - 1):
  
      decompress_thread = threading.Thread(target=decompress_video_data, 
  
          args=(frame_queue, frame_idxs, full_path))
  
      decompress_threads.append(decompress_thread)
  
      decompress_thread.start()

  The program will sucessfuly decompress approximately 200 frames, and then ImageIO will throw an RuntimeError : Could not read frame. The full error is here. Does anyone know why this is happening ? Is it possible to do what I’m trying to do ? Does ffmpeg just not work with multi threading ?

• Need Help Making Java Script Discord Music Bot

  2 février 2017, par Gambino

  I have tried to use this code to make a discord music bot but i am getting error telling me i need ffmpeg, but how would I implement it into this code ?

  index.js file

  const Discord = require('discord.js');
  
  const bot = new Discord.Client();
  
  const config = require("./config.json");
  
  const ytdl = require('ytdl-core');
  
  
  
  var youtube = require('./youtube.js');
  
  
  
  
  
  var ytAudioQueue = [];
  
  var dispatcher = null;
  
  
  
  bot.on('message', function(message) {
  
      var messageParts = message.content.split(' ');
  
      var command = messageParts[0].toLowerCase();
  
      var parameters = messageParts.splice(1, messageParts.length);
  
  
  
      switch (command) {
  
  
  
          case "-join" : 
  
          message.reply("Attempting to join channel " + parameters[0]);
  
          JoinCommand(parameters[0], message);
  
          break;
  
      
  
          case "-play" :
  
          PlayCommand(parameters.join(" "), message);
  
          break;
  
  
  
          case "-playqueue":
  
          PlayQueueCommand(message);
  
          break;
  
      }
  
  });
  
  
  
  
  
      function PlayCommand(searchTerm) {
  
          if(bot.voiceConnections.array().length == 0) {
  
              var defaultVoiceChannel = bot.channels.find(val => val.type === 'voice').name;
  
              JoinCommand(defaultVoiceChannel);
  
          }
  
          youtube.search(searchTerm, QueueYtAudioStream);
  
      }
  
  
  
      function PlayQueueCommand(message) {
  
          var queueString = "";
  
  
  
          for(var x = 0; x < ytAudioQueue.length; x++) {
  
              queueString += ytAudioQueue[x].videoName + ", ";
  
          }
  
          queueString = queueString.substring(0, queueString.length - 2);
  
          message.reply(queueString);
  
      }
  
  
  
      function JoinCommand(ChannelName) {
  
          var voiceChannel = GetChannelByName(ChannelName);
  
  
  
          if (voiceChannel) {
  
              voiceChannel.join();
  
              console.log("Joined " + voiceChannel.name);
  
          }
  
          
  
          return voiceChannel;
  
          
  
      }
  
  
  
      /* Helper Methods */
  
  
  
      function GetChannelByName(name) {
  
          var channel = bot.channels.find(val => val.name === name);
  
          return channel;
  
      }
  
  
  
    
  
  
  
      function QueueYtAudioStream(videoId, videoName) {
  
          var streamUrl = youtube.watchVideoUrl + videoId;
  
  
  
          if (!ytAudioQueue.length) {
  
              ytAudioQueue.push(
  
                  {
  
                      'streamUrl' : streamUrl,
  
                      'videoName' : videoName
  
                  }
  
              );
  
              console.log('Queued audio ' + videoName);
  
              PlayStream(ytAudioQueue[0].streamUrl);
  
          }
  
          else {
  
              ytAudioQueue.push(
  
                  {
  
                      'streamUrl' : streamUrl,
  
                      'videoName' : videoName
  
                  }
  
              );
  
          }
  
          console.log("Queued audio " + videoName);
  
      }
  
  
  
      function PlayStream(streamUrl) {
  
          const streamOptions = {seek: 0, volume: 1};
  
  
  
          if (streamUrl) {
  
              const stream = ytdl(streamUrl, {filter: 'audioonly'});
  
  
  
              if (dispatcher == null) {
  
                  var voiceConnection = bot.voiceConnections.first();
  
  
  
                  if(voiceConnection) {
  
                      console.log("Now Playing " + ytAudioQueue[0].videoname);
  
                      dispatcher = bot.voiceConnections.first().playStream(stream, streamOptions);
  
  
  
                      dispatcher.on('end', () => {
  
                          dispatcher = null;
  
                          PlayNextStreamInQueue();
  
                      });
  
  
  
                      dispatcher.on('error', (err) => {
  
                          console.log(err);
  
                      });
  
                  }
  
              } else {
  
                  dispatcher = bot.voiceConnections.first().playStream(stream, streamOptions);
  
              }
  
              
  
          }
  
      }
  
  
  
      function PlayNextStreamInQueue() {
  
          ytAudioQueue.splice(0, 1);
  
  
  
          if (ytAudioQueue.length != 0) {
  
              console.log("now Playing " + ytAudioQueue[0].videoName);
  
              PlayStream(ytAudioQueue[0].streamUrl);
  
          }
  
      }
  
  
  
  
  
  bot.login(config.token);

  youtube.js file

  var request = require('superagent');
  
  
  
  const API_KEY = "My API KEY";
  
  const WATCH_VIDEO_URL = "https://www.youtube.com/watch?v=";
  
  
  
  exports.watchVideoUrl = WATCH_VIDEO_URL;
  
  
  
  exports.search = function search(searchKeywords, callback) {
  
    var requestUrl = 'https://www.googleapis.com/youtube/v3/search' + '?part=snippet&q=' + escape(searchKeywords) + '&key=' + API_KEY;
  
  
  
    request(requestUrl, (error, response) => {
  
      if (!error && response.statusCode == 200) {
  
  
  
        var body = response.body;
  
        if (body.items.length == 0) {
  
          console.log("I Could Not Find Anything!");
  
          return;
  
        }
  
        for (var item of body.items) {
  
          if (item.id.kind == 'youtube#video') {
  
            callback(item.id.videoId, item.snippet.title);
  
            return;
  
          }
  
        }
  
      } else {
  
        console.log("Unexpected error!");
  
        return;
  
      }
  
    });
  
  
  
    return;
  
  
  
  };

  Error I am getting when I try to run code :

  Joined General

  C :\Discord Bot\node_modules\discord.js\src\client\voice\pcm\FfmpegConverterEngine.

  js:80

  throw new Error(

  ^

  Error : FFMPEG was not found on your system, so audio cannot be played. Please make
  sure FFMPEG is installed and in your PATH.

• How to fetch live video frame and its timestamp from ffmpeg to python

  15 février 2017, par vijiboy

  Searching for an alternative as OpenCV would not provide timestamps for live camera stream, which are required in my computer vision algorithm, I found this excellent article https://zulko.github.io/blog/2013/09/27/read-and-write-video-frames-in-python-using-ffmpeg/

  Working up the code on windows I still could’nt get the frame timestamps.
  I recollected seeing on ffmpeg forum somewhere that the video filters like showinfo are bypassed when redirected. Is this why the following code does not work as expected ?

  Expected : It should write video frames to disk as well as print timestamp details.
  Actual : It writes video files but does not get the timestamp (showinfo) details.

  Here’s the code I tried :

  import subprocess as sp
  
  import numpy
  
  import cv2
  
  
  
  command = [ 'ffmpeg', 
  
              '-i', 'e:\sample.wmv',
  
              '-pix_fmt', 'rgb24',
  
              '-vcodec', 'rawvideo',
  
              '-vf', 'showinfo', # video filter - showinfo will provide frame timestamps
  
              '-an','-sn', #-an, -sn disables audio and sub-title processing respectively
  
              '-f', 'image2pipe', '-'] # we need to output to a pipe
  
  
  
  pipe = sp.Popen(command, stdout = sp.PIPE, stderr = sp.STDOUT) # TODO someone on ffmpeg forum said video filters (e.g. showinfo) are bypassed when stdout is redirected to pipes??? 
  
  
  
  for i in range(10):
  
      raw_image = pipe.stdout.read(1280*720*3)
  
      img_info = pipe.stdout.read(244) # 244 characters is the current output of showinfo video filter
  
      print "showinfo output", img_info
  
      image1 =  numpy.fromstring(raw_image, dtype='uint8')
  
      image2 = image1.reshape((720,1280,3))  
  
  
  
      # write video frame to file just to verify
  
      videoFrameName = 'Video_Frame{0}.png'.format(i)
  
      cv2.imwrite(videoFrameName,image2)
  
  
  
      # throw away the data in the pipe's buffer.
  
      pipe.stdout.flush()

  So how to still get the frame timestamps from ffmpeg into python code so that it can be used in my computer vision algorithm...